In conclusion, FW-smoothing has a cost per iteration similar to the standard Frank-Wolfe algorithm for ranking with smooth objective functions. The cost of the non-smoothness of the objective function is a convergence rate of \(1/\sqrt{T}\) , while the Frank-Wolfe algorithm converges in \(O(1/T)\)  when the objective is smooth [1]}.
